Research On Workflow Mining Based On Multi-Perspective

Workflow is a technology imposing computer technique to execute parts ofor the whole business process within organization automatically. Through thedisposing efficiency and executing quality of process can be improved greatly.However, the complexity of the workflow management system increases thedifficulty of the workflow modeling. The goal of workflow mining is to reversethe process and collect data at runtime to support workflow design and analysis.So workflow mining technology which can improve efficiency and rationality inworkflow management system become more and more important in the workflowmethodology.Based on current research on workflow mining technology, origin ofworkflow mining technology and related evolution, some shortcomings needed tobe overcome in this field is pointed out. To provide solution for some of theproblems that described above, new algorithms and solutions for miningworkflow models are proposed in the workflow control-flow perspective,caseperspective and organizational perspective respectively. The main research resultsare as follows:1) In the workflow control-flow perspective field, a new algorithm formining workflow models is proposed. First, the definition of Workflow-modelDirect-depend Matrix(WDM) is proposed, and an algorithm is designed to set upWDM from workflow logs, at the same time, another algorithm is designed toautomate the modeling based on WDM. And according to the given example, thesignificant advantage of this algorithm will be found in improving accuracy,enhancing description ability. In another side of control-flow mining technology,to improve workflow for adapting to the uncertainty, the workflow frequentpattern is used. First, the frequent pattern discovery problem is defined, and afrequent pattern mining algorithm based on Apriori algorithm is proposed.2) In the workflow case perspective field, analyzed how data attributesinfluence the choices made in the process instances based on workflow logs.Mining process model in workflow logs based on-algorithm,analyzed thedecision point in process model, detection decision rule that affected the routingof a case through techniques based on decision tree analyze and data attributes inthe workflow logs. Discussed problems related to real-life decision rule mining,an improved algorithm is presented. To verify the presented ideas a test program has been implemented. The test result shows the alogrithm can correctly miningthe decision rule from workflow logs.3) In the workflow organizational perspective field, define metrics toestablish the relationships among originators by analyzing the information in theworkflow logs. Four methods for mining organizational structure from workflowlogs are presented in this paper, default mining,mining based on the causality,mining based on the similarity of activities and mining based on the similarity ofcases. By applying these methods, can construct the corresponding organizationalnetwork which reflects the organizational entities involved in the workflowprocess and corrects presented the organizational structure, and give an exampleto explain it.4) Based on the above research work, a workflow logs mining and analysissystem LogMiner has been designed and realized. The design architecture of theLogMiner is described in detail. For a large enterprise workflow logs carried out adetailed mining and analysis. The problems of business processes and bottleneckrestricting the business development are found from the mining results, and makeappropriate recommendations to improve the business processes, the enterprisebusiness processes processing capacity and work efficiency have been improved.